BIG DATA

BIGDATA , collection of large and complex data sets difficult to process usingon-hand database tools

V V V

WHY IS IT INTRODUCED

Lots of data is being collected & warehoused.

Processing exceeds database system capacity.

Structured & Unstructured data Separation of data from application. Understanding data analytics. Faster development, faster runtime. Elastic Feature-Level Scalability.

APACHE HADOOP

Provides massive scalable storage, its not a

database Data Processing Platform HDFS, a fault tolerant storage Store data in native format Reduce cost & lower risks Extracting business value from data Deliver new insights Automatically handles s/w & h/w failures

HDFS

Fault tolerant storage Survive failure on disk, network and network

interface Uses Map-Reduce programs Creates clusters of machines and co-ordinates

Storage on clusters using blocks No special hardware compared to RAID

PROBLEMS WITH BIG DATA

Will be so overwhelmed Costs escalate too fast Storage consumed 3 times Timeliness Analysis Poor data locality Incompatible & Replicated data

CONCLUSION

Big Data will replace the approaches, tools and

systems that underpin development work. Better analysis of the large volumes of data.

Potential for advancing in many scientific

disciplines. Improving the profitability. Technical challenges to be addressed dynamically

REFERENCES

www.bigdatauniversity.com www.sas.com/big-data/ en.wikipedia.org/wiki/Big_data cra.org/ccc/docs/init/bigdatawhitepaper.pdf dataanalyticssummit.com hadoop.apache.org

THANK YOU

Today’s Big Data Is Not Tomorrow’s Big Data